6105 Gates Hillman Center, Carnegie Mellon University
PITTSBURGH, PA 15213
I am a third year PhD student in the Computer Science Department of Carnegie Mellon University (CMU). I am fortunate to be advised by Zico Kolter. My interests lie in the algorithmic and foundational aspects of Machine Learning and Artificial Intelligence. Currently I am working on theoretically understanding Generative Adversarial Networks and Deep Learning. In the past I have worked in Learning Theory, Multi-Agent Systems and Reinforcement Learning.
I completed my undergraduate studies in the Department of Computer Science and Engineering at the Indian Institute of Technology, Chennai, India. Here I was advised by Balaraman Ravindran with whom I worked in Reinforcement Learning.
Here is a link to my CV.
Full Conference Papers
Vaishnavh Nagarajan and J. Zico Kolter, “Gradient descent GAN optimization is locally stable”, Neural Information Processing Systems (NIPS) 2017 [arxiv]
Maria-Florina Balcan, Avrim Blum and Vaishnavh Nagarajan, “Lifelong Learning in Costly Feature Spaces”, Algorithmic Learning Theory (ALT) 2017 [arxiv]
Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik and Colin White, “Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems”, Conference On Learning Theory (COLT), 2017 [arxiv]
(Double 1st author) V. Nagarajan, L. S. Marcolino, M. Tambe. “Every team deserves a second chance: Identifying when things go wrong”, Autonomous Agents and Multiagent Systems (AAMAS 2015), May 2015. [PDF] [Appendix]
- (Triple 1st author) A. Garlapati, A. Raghunathan, V. Nagarajan and B. Ravindran. “A Reinforcement Learning Approach to Online Learning of Decision Trees”, European Workshop on Reinforcement Learning (EWRL 2015 - ICML), Lille, France, July 2015. [PDF]
Short Papers and Demonstrations
- V. Nagarajan, B. Ravindran, “Knows-What-It-Knows Inverse Reinforcement Learning”. Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2015), Edmonton, Alberta, Canada, June 2015 [PDF]
Last Updated: Oct 6th, 2017